Selection in Massively Parallel Genetic Algorithms

The availability of massively parallel computers makes it possible to apply genetic algorithms to large populations and very complex applications. Among these applications are studies of natural evolution in the emerging eld of articial life, which place special demands on the genetic algorithm. In this paper, we characterize the di erence between panmictic and local selection/mating schemes in terms of diversity of alleles, diversity of genotypes, the inbreeding coe cient, and the speed and robustness of the genetic algorithm. Based on these metrics, local mating appears to not only be superior to panmictic for arti cial evolutionary simulations, but also for more traditional applications of genetic algorithms. In Proceedings of the Fourth International Conference on Genetic Algorithms. Morgan Kaufmann, 1991.

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